Continuing advances of physical-layer technologies have enabled WiFi to support high data-rates at low cost and hence become widely deployed in networking infrastructures and mobile devices, such as laptops, smartphones, netbooks, and tablet PCs. Despite its high performance and inexpensive availability, the energy-efficiency of WiFi remains a challenging problem. For instance, WiFi accounts for more than 10% of the energy consumption in current laptops. It may also raise a GSM cellphone's power consumption 14 times even without packet transmissions.
WiFi's energy-inefficiency comes from its intrinsic CSMA mechanism—the radio must perform idle listening (IL) continuously, in order to detect unpredictably arriving packets or assess a clear channel. The power consumption of IL, unfortunately, is comparable to that of active transmission/reception. Even worse, WiFi clients tend to spend a large fraction of time in IL, due to MAC-level contention and network-level delay. Therefore, minimizing the IL's energy consumption is crucial to WiFi's energy-efficiency.
A natural way to reduce the IL's energy cost is sleep scheduling. In WiFi's power-saving mode (PSM) and its variants, clients can sleep adaptively, and wake up only when they intend to transmit, or expect to receive packets. The AP buffers downlink packets and transmits only after the client wakes up. PSM essentially shapes the traffic by aggregating downlink packets, thereby reducing the receiver's wait time caused by the network-level latency. However, it cannot reduce the IL time associated with carrier sensing and contention. Through an extensive trace-based analysis of real WiFi networks, it was found that IL still dominates the clients' energy consumption even with PSM enabled: it accounts for more than 80% of energy consumption for clients in a busy network and 60% in a relatively idle network.
Since the IL time cannot be reduced any further due to WiFi's CSMA, an additional dimension—reducing IL power consumption—is exploited in order to minimize its energy cost. Ideally, if the exact idle period is known, the radio could be powered off or put to sleep during IL, and wake up and process packets on demand. However, due to the distributed and asynchronous nature of CSMA, the idle time between packets varies widely and unpredictably. Under-estimation of an idle interval will waste the mobile device's energy, while an over-estimation causes the radio to drop all incoming packets during the sleep.
Therefore, it is desirable to reduce the power consumption during the idle listening period and thereby reduce the power consumption of wireless mobile devices. This section provides background information related to the present disclosure which is not necessarily prior art.